For Task 3, make a map of land use / land cover and watersheds for the big island of Hawaii.
Familiarize yourself with the data attributes (see link), and download the shapefile data for each. After reading the shapefile data into R, make finalized map(s) in which you:
There is flexibility! You can decide:
Whatever you decide is great, just make sure that your final outputs are presented in a nice professional HTML that you’d be proud to share with someone so that they can see your awesome spatial code!
library(tidyverse)
library(janitor)
library(kableExtra)
library(naniar)
library(skimr)
library(sf)
library(tmap)
library(paletteer)
library(lubridate)
library(here)
watershed <- read_sf(dsn = here(".", "Watersheds"),
layer = "Watersheds") %>%
st_transform(crs = 6628)
lulc <- read_sf(dsn = here(".", "Land_Use_Land_Cover_LULC"),
layer = "Land_Use_Land_Cover_LULC") %>%
st_transform(crs = 6628)
# ggplot(data = watershed) +
# geom_sf(color = "black",
# size = 0.1) +
# geom_sf(data = lulc,
# aes(fill = landcover),
# alpha = 0.5,
# color = "NA",
# show.legend = FALSE) +
# theme_minimal()
#hawaii_clip <- st_intersection(watershed, lulc)
hawaii_clip_tmap <- tm_basemap("Esri.WorldImagery") + # Put in a basemap
tm_shape(watershed) +
tm_borders("lightblue", lwd = .5) +
tm_shape(lulc) +
tm_fill("landcover", palette = c("orange", "purple", "yellow"), alpha = 0.5) +
tm_layout("Land Use/Land Cover for Watersheds of the Hawaiian Islands",
main.title.position = "center") +
tm_view(view.legend.position = "NA") +
tm_legend(outside=TRUE)
tmap_mode("view") # Sets it to interactive view
hawaii_clip_tmap